China’s constantly rapid economic growth accompanying by a low overall inflation has long been mysterious in macroeconomics. The core purpose of this paper is to solve this puzzle. Therefore, we integrate overdetermined set of equations into a MUCSVO model to explore the volatility mechanism of the overall inflation from a sectoral perspective. Our key findings include: 1) the hedging effect of sectoral inflation fluctuations principally accounts for China’s long-run stable overall inflation; 2) the main contradiction of China’s inflation has been shifting from high price levels in the traditional food and residence categories to rising prices in the health care category; 3) as the proportions of inflation in the food and residence categories fall steadily, sectoral inflation weights become more evenly distributed. In conclusion, China’s overall inflation and deflation will be much less likely to occur, while inflation is still of sectoral imbalance. Unusual price fluctuations in the food and health care categories, which are highly relevant to basic living standards of the low-income group, deserve close attention in particular. Overall, besides solving the puzzle of China’s low inflation, our model is applicable to economies that do not publish inflation weights, which is a useful extension of core inflation measurement.
{"title":"SOLVING THE PUZZLE OF CHINA’S LOW INFLATION: A NEW PERSPECTIVE FROM SECTORAL CORE INFLATION FLUCTUATIONS","authors":"Dayu Liu, Bin Xu, Yang Song, Tingyu Liu","doi":"10.3846/tede.2024.20532","DOIUrl":"https://doi.org/10.3846/tede.2024.20532","url":null,"abstract":"China’s constantly rapid economic growth accompanying by a low overall inflation has long been mysterious in macroeconomics. The core purpose of this paper is to solve this puzzle. Therefore, we integrate overdetermined set of equations into a MUCSVO model to explore the volatility mechanism of the overall inflation from a sectoral perspective. Our key findings include: 1) the hedging effect of sectoral inflation fluctuations principally accounts for China’s long-run stable overall inflation; 2) the main contradiction of China’s inflation has been shifting from high price levels in the traditional food and residence categories to rising prices in the health care category; 3) as the proportions of inflation in the food and residence categories fall steadily, sectoral inflation weights become more evenly distributed. In conclusion, China’s overall inflation and deflation will be much less likely to occur, while inflation is still of sectoral imbalance. Unusual price fluctuations in the food and health care categories, which are highly relevant to basic living standards of the low-income group, deserve close attention in particular. Overall, besides solving the puzzle of China’s low inflation, our model is applicable to economies that do not publish inflation weights, which is a useful extension of core inflation measurement.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140241244","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Despite the extensive research on sustainability dimensions, the researcher has not completely addressed all the dimensions of sustainability. Most of the times, sustainability is considered as a whole variable, however, the work on separate dimensions is lacking in the literature. Particularly, human sustainability is rarely addressed by the previous studies. Additionally, various dimensions of sustainability such as social, economic, environmental and human is rarely tested in relation to the organizational resilience. Therefore, to fill this gap, this study considered to examine the role of organizational resilience in social sustainability, economic sustainability, environmental sustainability and human sustainability in a sample of FMCG employees. The study used non-probability snowball sampling to collect data from managerial level employees. Data analysis is carried out by using SPSS. Findings identified that; organizational resilience has influential role in various dimensions of sustainability. The focus of the policymakers on organizational resilience can increase the socio-economic and environmental sustainability. The operational efficiency can strengthen the relationship between organizational resilience and sustainability.
{"title":"THE ROLE OF ORGANIZATIONAL RESILIENCE IN SOCIAL, ECONOMIC, ENVIRONMENTAL AND HUMAN SUSTAINABILITY: EVIDENCE FORM CHINESE FMCG SECTOR","authors":"Ming Xu, Qiang Xu, Sheng Wei, Lei Cong","doi":"10.3846/tede.2024.20476","DOIUrl":"https://doi.org/10.3846/tede.2024.20476","url":null,"abstract":"Despite the extensive research on sustainability dimensions, the researcher has not completely addressed all the dimensions of sustainability. Most of the times, sustainability is considered as a whole variable, however, the work on separate dimensions is lacking in the literature. Particularly, human sustainability is rarely addressed by the previous studies. Additionally, various dimensions of sustainability such as social, economic, environmental and human is rarely tested in relation to the organizational resilience. Therefore, to fill this gap, this study considered to examine the role of organizational resilience in social sustainability, economic sustainability, environmental sustainability and human sustainability in a sample of FMCG employees. The study used non-probability snowball sampling to collect data from managerial level employees. Data analysis is carried out by using SPSS. Findings identified that; organizational resilience has influential role in various dimensions of sustainability. The focus of the policymakers on organizational resilience can increase the socio-economic and environmental sustainability. The operational efficiency can strengthen the relationship between organizational resilience and sustainability.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140237603","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The widespread and substantial effect of the global financial crisis in history underlines the importance of forecasting financial crisis effectively. In this paper, we propose temporal convolutional network (TCN), which based on a convolutional neural network, to construct an early warning system for financial crises. The proposed TCN is compared with logit model and other deep learning models. The Shapley value decomposition is calculated for the interpretability of the early warning system. Experimental results show that the proposed TCN outperforms other models, and the stock price and the real GDP growth have the largest contributions in the crises prediction.
全球金融危机在历史上造成的广泛而巨大的影响凸显了有效预测金融危机的重要性。本文提出了基于卷积神经网络的时序卷积网络（TCN）来构建金融危机预警系统。本文将时序卷积网络与 logit 模型和其他深度学习模型进行了比较。为了提高预警系统的可解释性，计算了 Shapley 值分解。实验结果表明，所提出的 TCN 优于其他模型，其中股票价格和实际 GDP 增长对危机预测的贡献最大。
{"title":"AN EARLY WARNING SYSTEM FOR FINANCIAL CRISES: A TEMPORAL CONVOLUTIONAL NETWORK APPROACH","authors":"Shun Chen, Yi Huang, Lei Ge","doi":"10.3846/tede.2024.20555","DOIUrl":"https://doi.org/10.3846/tede.2024.20555","url":null,"abstract":"The widespread and substantial effect of the global financial crisis in history underlines the importance of forecasting financial crisis effectively. In this paper, we propose temporal convolutional network (TCN), which based on a convolutional neural network, to construct an early warning system for financial crises. The proposed TCN is compared with logit model and other deep learning models. The Shapley value decomposition is calculated for the interpretability of the early warning system. Experimental results show that the proposed TCN outperforms other models, and the stock price and the real GDP growth have the largest contributions in the crises prediction.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140239862","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Guangliang Liu, Wenfeng Ge, Xiaodong Yang, Asif Razzaq, Xufeng Su, Qiying Ran, Yang Xu
Low-carbon transformation of the economy is the inevitable orientation of socialism with Chinese characteristics to high-quality development in the new era, while the Chinese decentralized development model determines that the competition of local governments in China is an important factor influencing the green technological innovation on low-carbon transformation of the economy. How to achieve coordinated economic growth and ecological environment has become a prob-lem for local governments. Data from a Chinese provincial panel covering the years 2007–2019 is used to investigate the effects of heterogeneous local government competition (Comp), namely, economic, ecological and service competitions on economic low-carbon transition, and moderating effects of heterogeneous government competition and green technology innovation (GTECH) on the low-carbon economic transition (LCT). The results reveal that there are substantial disparities in the consequences of heterogeneous government competition on low-carbon economic transition (LCT). Among them, economic competition significantly dampens economic low-carbon transition (LCT), and ecological competition and service competition significantly boost economic low-carbon transi-tion (LCT). After performing robustness checks, these results continue to be strongly convincing. The study of moderating effects shows that economic competition can dampen the positive influence of green technology innovation (GTECH) to the economic low-carbon transition (LCT). However, ecological competition and service competition facilitate the promoting effect of green technology innovation on economic low-carbon transition (LCT).
{"title":"IMPACT OF HETEROGENEOUS LOCAL GOVERNMENT COMPETITION AND GREEN TECHNOLOGY INNOVATION ON ECONOMIC LOW-CARBON TRANSITION: NEW INSIGHTS FROM CHINA","authors":"Guangliang Liu, Wenfeng Ge, Xiaodong Yang, Asif Razzaq, Xufeng Su, Qiying Ran, Yang Xu","doi":"10.3846/tede.2024.20776","DOIUrl":"https://doi.org/10.3846/tede.2024.20776","url":null,"abstract":"Low-carbon transformation of the economy is the inevitable orientation of socialism with Chinese characteristics to high-quality development in the new era, while the Chinese decentralized development model determines that the competition of local governments in China is an important factor influencing the green technological innovation on low-carbon transformation of the economy. How to achieve coordinated economic growth and ecological environment has become a prob-lem for local governments. Data from a Chinese provincial panel covering the years 2007–2019 is used to investigate the effects of heterogeneous local government competition (Comp), namely, economic, ecological and service competitions on economic low-carbon transition, and moderating effects of heterogeneous government competition and green technology innovation (GTECH) on the low-carbon economic transition (LCT). The results reveal that there are substantial disparities in the consequences of heterogeneous government competition on low-carbon economic transition (LCT). Among them, economic competition significantly dampens economic low-carbon transition (LCT), and ecological competition and service competition significantly boost economic low-carbon transi-tion (LCT). After performing robustness checks, these results continue to be strongly convincing. The study of moderating effects shows that economic competition can dampen the positive influence of green technology innovation (GTECH) to the economic low-carbon transition (LCT). However, ecological competition and service competition facilitate the promoting effect of green technology innovation on economic low-carbon transition (LCT).","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140242926","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This article examines how different forms of digitalization affect inequality in Europe. Using a cross-national dataset of economic development and digitalization across a range of regression specifications including country and time fixed effects, this article explores the heterogeneous relationships of disparate forms of digitalization – human capital, broadband connectivity, integration of digital technology into small and medium enterprises, and digital public services – with income inequality. Fixed country and time effects models show that only the digitalization of human capital and integration of digital technology by SMEs are associated with decreases in income inequality. Causal mediation analysis reveals that tertiary education, despite its oft-cited connection to digital technology uptake, has no causal effect on the pathways through which digitalization of labour and SME operations lower inequality, which are direct. The findings tentatively suggest that there exist informal sources of digital skills training apart from formal tertiary education and point to SMEs as a potentially impactful area for investing in digitalization as pathways for income redistribution.
{"title":"HOW DO DIFFERENT FORMS OF DIGITALIZATION AFFECT INCOME INEQUALITY?","authors":"Anson Au","doi":"10.3846/tede.2024.20562","DOIUrl":"https://doi.org/10.3846/tede.2024.20562","url":null,"abstract":"This article examines how different forms of digitalization affect inequality in Europe. Using a cross-national dataset of economic development and digitalization across a range of regression specifications including country and time fixed effects, this article explores the heterogeneous relationships of disparate forms of digitalization – human capital, broadband connectivity, integration of digital technology into small and medium enterprises, and digital public services – with income inequality. Fixed country and time effects models show that only the digitalization of human capital and integration of digital technology by SMEs are associated with decreases in income inequality. Causal mediation analysis reveals that tertiary education, despite its oft-cited connection to digital technology uptake, has no causal effect on the pathways through which digitalization of labour and SME operations lower inequality, which are direct. The findings tentatively suggest that there exist informal sources of digital skills training apart from formal tertiary education and point to SMEs as a potentially impactful area for investing in digitalization as pathways for income redistribution.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140243518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The green credit policy (GCP) is an institutional framework aimed at guiding enterprises towards green transformation and promoting high-quality development, which serves as a crucial tool for supporting the establishment of a green technology innovation system. In this study, utilizing the green credit guidelines as a quasi-natural experiment and constructed a continuous difference-in-difference (DID) model, examines the impact of GCP impact on enterprise green innovation and its internal mechanisms by analyzing data from Chinese A-share listed companies between 2006 and 2021. Our findings indicate that the GCP had a significant impact on enterprise green innovation, inhibiting companies from in-dependently developing green innovation while promoting joint green innovation with other institutions; These results were robust and consistent, even after conducting several sensitiv-ity analyses; This mechanism indicate that the commercial credit plays an important regulatory role in the process of GCP affecting green innovation of enterprises and the financing constraints act as an intermediary factor in the process of GCP affecting green innovation. Based on our research, we offer policy recommendations aimed at improving the GCP and fostering a market-oriented green technology innovation system.
{"title":"CAN THE GREEN CREDIT POLICY PROMOTE GREEN INNOVATION IN ENTERPRISES? EMPIRICAL EVIDENCE FROM CHINA","authors":"Xu Fang, Maotao Liu, Guangqin Li","doi":"10.3846/tede.2024.20497","DOIUrl":"https://doi.org/10.3846/tede.2024.20497","url":null,"abstract":"The green credit policy (GCP) is an institutional framework aimed at guiding enterprises towards green transformation and promoting high-quality development, which serves as a crucial tool for supporting the establishment of a green technology innovation system. In this study, utilizing the green credit guidelines as a quasi-natural experiment and constructed a continuous difference-in-difference (DID) model, examines the impact of GCP impact on enterprise green innovation and its internal mechanisms by analyzing data from Chinese A-share listed companies between 2006 and 2021. Our findings indicate that the GCP had a significant impact on enterprise green innovation, inhibiting companies from in-dependently developing green innovation while promoting joint green innovation with other institutions; These results were robust and consistent, even after conducting several sensitiv-ity analyses; This mechanism indicate that the commercial credit plays an important regulatory role in the process of GCP affecting green innovation of enterprises and the financing constraints act as an intermediary factor in the process of GCP affecting green innovation. Based on our research, we offer policy recommendations aimed at improving the GCP and fostering a market-oriented green technology innovation system.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140243632","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The aim of this paper is to examine the impact of a country’s entry into the monetary union on its economic variables growth rate of real GDP as well as on GDP per capita growth for the period from 2010 to 2020. The clustering method and the ANFIS method were used in the data analysis. A total of two cluster analyses were performed. The first cluster includes countries that joined the EU in 2004 and became EZ members by 2010. The second cluster refers to those countries that joined the EU in 2004 but are not yet members of the EZ. For the first individual cluster analysis two models were analysed and for the second individual cluster three models were analysed using the ANFIS method. As expected, the results showed that GDP growth is connected with trade, inflation and gross investments in fixed capital in the observed countries, while GDP per capita is connected with unemployment, interest rates and public debt. With regard to GDP growth, the difference between countries that are in the eurozone and those that are not is not significant, which is in line with other studies.
本文旨在研究一个国家加入货币联盟对其 2010 年至 2020 年期间实际 GDP 增长率以及人均 GDP 增长率等经济变量的影响。数据分析中使用了聚类方法和 ANFIS 方法。共进行了两次聚类分析。第一个聚类包括 2004 年加入欧盟并在 2010 年成为 EZ 成员的国家。第二个聚类指的是 2004 年加入欧盟但尚未成为 EZ 成员的国家。对于第一个单个群组分析，使用 ANFIS 方法分析了两个模型；对于第二个单个群组分析，使用 ANFIS 方法分析了三个模型。正如预期的那样，分析结果表明，在所观察的国家中，国内生产总值的增长与贸易、通货膨胀和固定资本投资总额有关，而人均国内生产总值与失业率、利率和公共债务有关。在国内生产总值增长方面，欧元区国家与非欧元区国家之间的差异并不显著，这与其他研究结果一致。
{"title":"MEASURING THE EFFECT OF ENTRY INTO THE EUROZONE ON ECONOMIC GROWTH – DATA STORYTELLING USING CLUSTERING AND ANFIS","authors":"Jurica Bosna, Sonja Brlečić Valčić, Anita Peša","doi":"10.3846/tede.2024.20584","DOIUrl":"https://doi.org/10.3846/tede.2024.20584","url":null,"abstract":"The aim of this paper is to examine the impact of a country’s entry into the monetary union on its economic variables growth rate of real GDP as well as on GDP per capita growth for the period from 2010 to 2020. The clustering method and the ANFIS method were used in the data analysis. A total of two cluster analyses were performed. The first cluster includes countries that joined the EU in 2004 and became EZ members by 2010. The second cluster refers to those countries that joined the EU in 2004 but are not yet members of the EZ. For the first individual cluster analysis two models were analysed and for the second individual cluster three models were analysed using the ANFIS method. As expected, the results showed that GDP growth is connected with trade, inflation and gross investments in fixed capital in the observed countries, while GDP per capita is connected with unemployment, interest rates and public debt. With regard to GDP growth, the difference between countries that are in the eurozone and those that are not is not significant, which is in line with other studies.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140242408","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Housing industry is one of the major threats to global environment and resource depletion. Particularly in China, it is regarded as a major challenge due to massive population growth. The most common barriers involve; economic barriers and environmental barriers. Therefore, to promote sustainable housing development, the management of these barriers is most crucial. This study is an attempt to overcome these barriers with the help of financial institutions in the context of China. The sample of the study are construction sector employees which are selected through simple random sampling method. Partial Least Square (PLS) is employed as statistical tool to analyze the primary data. Results revealed the positive role of financial institutions to overcome the challenges related to the economic barriers and environmental barriers. Financing from banks for the sustainable housing schemes can reduce the economic barriers and help to fulfil the sustainable housing criteria. Similarly, the environment requirements can also be achieved through environmental policy developed by the banks in China. This study recommended the Chinese government to promote sustainable hosing development through the promotion of bank financing and implementation of banks environmental policies.
{"title":"SUSTAINABLE HOUSING DEVELOPMENT IN CHINA: DOES FINANCIAL INSTITUTIONS OVERCOME THE RISKS AND CHALLENGES TO SUSTAINABLE HOUSING?","authors":"Shaodong Ma","doi":"10.3846/tede.2024.20581","DOIUrl":"https://doi.org/10.3846/tede.2024.20581","url":null,"abstract":"Housing industry is one of the major threats to global environment and resource depletion. Particularly in China, it is regarded as a major challenge due to massive population growth. The most common barriers involve; economic barriers and environmental barriers. Therefore, to promote sustainable housing development, the management of these barriers is most crucial. This study is an attempt to overcome these barriers with the help of financial institutions in the context of China. The sample of the study are construction sector employees which are selected through simple random sampling method. Partial Least Square (PLS) is employed as statistical tool to analyze the primary data. Results revealed the positive role of financial institutions to overcome the challenges related to the economic barriers and environmental barriers. Financing from banks for the sustainable housing schemes can reduce the economic barriers and help to fulfil the sustainable housing criteria. Similarly, the environment requirements can also be achieved through environmental policy developed by the banks in China. This study recommended the Chinese government to promote sustainable hosing development through the promotion of bank financing and implementation of banks environmental policies.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140243683","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Romeo-Victor Ionescu, M. Zlati, V. Antohi, Irina Susanu, Nicoleta Bărbuță-Mișu
The multiple global crisis has made the economies of the world’s countries, including EU’s economy, vulnerable through the downgrading of the pandemic and the subsequent outbreak of geo-political conflict. These two events had the effect of decelerating the European economy and increasing the poverty level of the population, even that these developments are weaker than in rest of the world. The main objective of the present scientific approach is to identify a risk function based on Markov probability chains and to assess the possibilities of economic recovery through a package of policies structured over different time horizons. The used methods consist of meta-analysis, statistical analysis and geo-spatial and temporal modelling. The results of the study capture the integrated developments of risk-generating macroeconomic elements such as inflation, unemployment, public debt growth in a regionally segregated manner. These elements are useful for supranational decision-makers to increase the economic survival rate after multiple shocks through our proposed policy package.
{"title":"QUANTIFYING THE ECONOMIC SURVIVE ACROSS THE EU USING MARKOV PROBABILITY CHAINS","authors":"Romeo-Victor Ionescu, M. Zlati, V. Antohi, Irina Susanu, Nicoleta Bărbuță-Mișu","doi":"10.3846/tede.2024.20760","DOIUrl":"https://doi.org/10.3846/tede.2024.20760","url":null,"abstract":"The multiple global crisis has made the economies of the world’s countries, including EU’s economy, vulnerable through the downgrading of the pandemic and the subsequent outbreak of geo-political conflict. These two events had the effect of decelerating the European economy and increasing the poverty level of the population, even that these developments are weaker than in rest of the world. The main objective of the present scientific approach is to identify a risk function based on Markov probability chains and to assess the possibilities of economic recovery through a package of policies structured over different time horizons. The used methods consist of meta-analysis, statistical analysis and geo-spatial and temporal modelling. The results of the study capture the integrated developments of risk-generating macroeconomic elements such as inflation, unemployment, public debt growth in a regionally segregated manner. These elements are useful for supranational decision-makers to increase the economic survival rate after multiple shocks through our proposed policy package.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140243792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper aims to identify the differences in the employment rate dynamics in economy sections, considering gender, in the European Union countries in 2020, compared to the 2008–2019 period. Two methods were used. The first method compares forecasts from models describing employment changes in the pre-pandemic periods with information concerning the actual employment rate in 2020, using three indices measuring the significance of the observed discrepancies. The second method uses dynamic cluster analysis for the 2008–2020 period, and evaluates the changes in composition of groups that occured in 2020. The proposed methods were applied separately to the data concerning the employment of females and males (employment rates) in the EU countries, always divided into economy sections and section groups (A, B-E, F, G-I, J, K, L, M and N, O-Q, R). The application of the “Triple 2 Rule” helped to identify the changes in the previous employment trends (“Interventions”). The evaluation of changes in the dynamics of the employment rate in total and in section groups and according to gender in the EU countries in 2020 – compared to the forecasts from the 2013–2019 trends – revealed that the EU labour market responded differently to the COVID-19 pandemic situation.
{"title":"COVID-19 IMPACT ON LABOUR MARKET IN EU COUNTRIES – DIFFERENCES IN MEN AND WOMEN EMPLOYMENT RATE TENDENCIES","authors":"M. Markowska, D. Strahl","doi":"10.3846/tede.2024.20811","DOIUrl":"https://doi.org/10.3846/tede.2024.20811","url":null,"abstract":"This paper aims to identify the differences in the employment rate dynamics in economy sections, considering gender, in the European Union countries in 2020, compared to the 2008–2019 period. Two methods were used. The first method compares forecasts from models describing employment changes in the pre-pandemic periods with information concerning the actual employment rate in 2020, using three indices measuring the significance of the observed discrepancies. The second method uses dynamic cluster analysis for the 2008–2020 period, and evaluates the changes in composition of groups that occured in 2020. The proposed methods were applied separately to the data concerning the employment of females and males (employment rates) in the EU countries, always divided into economy sections and section groups (A, B-E, F, G-I, J, K, L, M and N, O-Q, R). The application of the “Triple 2 Rule” helped to identify the changes in the previous employment trends (“Interventions”). The evaluation of changes in the dynamics of the employment rate in total and in section groups and according to gender in the EU countries in 2020 – compared to the forecasts from the 2013–2019 trends – revealed that the EU labour market responded differently to the COVID-19 pandemic situation.","PeriodicalId":51460,"journal":{"name":"Technological and Economic Development of Economy","volume":null,"pages":null},"PeriodicalIF":5.9,"publicationDate":"2024-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140242782","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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